IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v14y2022i10p283-d929501.html
   My bibliography  Save this article

FakeNewsLab: Experimental Study on Biases and Pitfalls Preventing Us from Distinguishing True from False News

Author

Listed:
  • Giancarlo Ruffo

    (Department of Computer Science, Università degli Studi di Torino, 10149 Torino, Italy
    Current affiliation: Department of Science and Technological Innovation (DISIT), Università del Piemonte Orientale, 15121 Alessandria, Italy.
    These authors contributed equally to this work.)

  • Alfonso Semeraro

    (Department of Computer Science, Università degli Studi di Torino, 10149 Torino, Italy
    These authors contributed equally to this work.)

Abstract

Misinformation posting and spreading in social media is ignited by personal decisions on the truthfulness of news that may cause wide and deep cascades at a large scale in a fraction of minutes. When individuals are exposed to information, they usually take a few seconds to decide if the content (or the source) is reliable and whether to share it. Although the opportunity to verify the rumour is often just one click away, many users fail to make a correct evaluation. We studied this phenomenon with a web-based questionnaire that was compiled by 7298 different volunteers, where the participants were asked to mark 20 news items as true or false. Interestingly, false news is correctly identified more frequently than true news, but showing the full article instead of just the title, surprisingly, does not increase general accuracy. Additionally, displaying the original source of the news may contribute to misleading the user in some cases, while the genuine wisdom of the crowd can positively assist individuals’ ability to classify news correctly. Finally, participants whose browsing activity suggests a parallel fact-checking activity show better performance and declare themselves as young adults. This work highlights a series of pitfalls that can influence human annotators when building false news datasets, which in turn can fuel the research on the automated fake news detection; furthermore, these findings challenge the common rationale of AI that suggest users read the full article before re-sharing.

Suggested Citation

  • Giancarlo Ruffo & Alfonso Semeraro, 2022. "FakeNewsLab: Experimental Study on Biases and Pitfalls Preventing Us from Distinguishing True from False News," Future Internet, MDPI, vol. 14(10), pages 1-24, September.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:10:p:283-:d:929501
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/14/10/283/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/14/10/283/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    2. Hunt Allcott & Matthew Gentzkow & Chuan Yu, 2019. "Trends in the Diffusion of Misinformation on Social Media," NBER Working Papers 25500, National Bureau of Economic Research, Inc.
    3. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leopoldo Fergusson & Carlos Molina, 2020. "Facebook Causes Protests," HiCN Working Papers 323, Households in Conflict Network.
    2. Michele Cantarella & Nicolo' Fraccaroli & Roberto Volpe, 2019. "Does fake news affect voting behaviour?," Department of Economics 0146, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    3. Bartosz Wilczek, 2020. "Misinformation and herd behavior in media markets: A cross-national investigation of how tabloids’ attention to misinformation drives broadsheets’ attention to misinformation in political and business," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.
    4. Laura Studen & Victor Tiberius, 2020. "Social Media, Quo Vadis? Prospective Development and Implications," Future Internet, MDPI, vol. 12(9), pages 1-22, August.
    5. Dr. Diala Edwin Lionel & Dr. Uzowuihe Bertha, 2024. "Visual Elements in Digital Technology Platforms and Visualized Communication in Spreading of False Information," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3s), pages 2118-2138, March.
    6. Andrew P. Weiss & Ahmed Alwan & Eric P. Garcia & Antranik T. Kirakosian, 2021. "Toward a Comprehensive Model of Fake News: A New Approach to Examine the Creation and Sharing of False Information," Societies, MDPI, vol. 11(3), pages 1-17, July.
    7. Raúl Rodríguez-Ferrándiz & Cande Sánchez-Olmos & Tatiana Hidalgo-Marí & Estela Saquete-Boro, 2021. "Memetics of Deception: Spreading Local Meme Hoaxes during COVID-19 1st Year," Future Internet, MDPI, vol. 13(6), pages 1-19, June.
    8. Matilde Giaccherini & Joanna Kopinska & Gabriele Rovigatti, 2022. "Vax Populi: The Social Costs of Online Vaccine Skepticism," CESifo Working Paper Series 10184, CESifo.
    9. Jost, Peter J. & Pünder, Johanna & Schulze-Lohoff, Isabell, 2020. "Fake news - Does perception matter more than the truth?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 85(C).
    10. Artem Zakharchenko & Tomáš Peráček & Solomiia Fedushko & Yuriy Syerov & Olha Trach, 2021. "When Fact-Checking and ‘BBC Standards’ Are Helpless: ‘Fake Newsworthy Event’ Manipulation and the Reaction of the ‘High-Quality Media’ on It," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    11. Ryan C. Moore & Ross Dahlke & Jeffrey T. Hancock, 2023. "Exposure to untrustworthy websites in the 2020 US election," Nature Human Behaviour, Nature, vol. 7(7), pages 1096-1105, July.
    12. Christopher Adamo & Jeffrey Carpenter, 2023. "Sentiment and the belief in fake news during the 2020 presidential primaries," Oxford Open Economics, Oxford University Press, vol. 2, pages 512-547.
    13. Shixiong Wang & Fangfang Su & Lu Ye & Yuan Jing, 2022. "Disinformation: A Bibliometric Review," IJERPH, MDPI, vol. 19(24), pages 1-21, December.
    14. Yesilada, Muhsin & Lewandowsky, Stephan, 2022. "Systematic review: YouTube recommendations and problematic content," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 11(1), pages 1-22.
    15. Giacomo Manetti & Carmela Nitti & Marco Bellucci, 2022. "The accountability of Search and Rescue NGOs," Working Papers - Business wp2022_02.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    16. Ka Chung Ng & Ping Fan Ke & Mike K. P. So & Kar Yan Tam, 2023. "Augmenting fake content detection in online platforms: A domain adaptive transfer learning via adversarial training approach," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2101-2122, July.
    17. Andrey Simonov & Szymon Sacher & Jean-Pierre Dubé & Shirsho Biswas, 2022. "Frontiers: The Persuasive Effect of Fox News: Noncompliance with Social Distancing During the COVID-19 Pandemic," Marketing Science, INFORMS, vol. 41(2), pages 230-242, March.
    18. Domenico, Giandomenico Di & Sit, Jason & Ishizaka, Alessio & Nunan, Daniel, 2021. "Fake news, social media and marketing: A systematic review," Journal of Business Research, Elsevier, vol. 124(C), pages 329-341.
    19. Xiangyu Wang & Min Zhang & Weiguo Fan & Kang Zhao, 2022. "Understanding the spread of COVID‐19 misinformation on social media: The effects of topics and a political leader's nudge," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(5), pages 726-737, May.
    20. Julia Cage & Nicolas Hervé & Marie-Luce Viaud, 2017. "The Production of Information in an Online World: Is Copy Right?," Working Papers hal-03393171, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:14:y:2022:i:10:p:283-:d:929501. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.